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COASTAL ALGORITHMS AND ON-DEMAND PROCESSING - THE LESSONS LEARNT FROM COASTCOLOUR FOR SENTINEL 3

机译:沿海算法和按需处理 - 从海岸Colour为Sentinel 3的经验教训

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The ESA DUE CoastColour Project has been initiated to provide water quality products for important costal zones globally. A new 5 component bio-optical model was developed and used in a 3-step approach for regional processing of ocean colour data. The L1P step consists of radiometric and geometric system corrections, and top-of-atmosphere pixel classification including cloud screening, sun glint risk masking or detection of floating vegetation. The second step includes the atmospheric correction and is providing the L2R product, which comprises marine reflectances with error characterisation and normalisation. The third step is the in-water processing which produces IOPs, attenuation coefficient and water constituent concentrations. Each of these steps will benefit from the additional bands on OLCI. The 5 component bio-optical model will already be used in the standard ESA processing of OLCI, and also part of the pixel classification methods will be part of the standard products. Other algorithm adaptation are in preparation. Another important advantage of the CoastColour approach is the highly configurable processing chain which allows adaptation to the individual characteristics of the area of interest, temporal window, algorithm parametrisation and processing chain configuration. This flexibility is made available to data users through the CoastColour on-demand processing service. The complete global MERIS Full and Reduced Resolution data archive is accessible, covering the time range from 17. May 2002 until 08. April 2012, which is almost 200TB of in-put data available online. The CoastColour on-demand processing service can serve as a model for hosted processing, where the software is moved to the data instead of moving the data to the users, which will be a challenge with the large amount of data coming from Sentinel 3.
机译:已启动ESA到期海岸COLUCOUR项目,为全球范围内为重要的肋骨区域提供水质产品。开发了一种新的5分量生物光学模型,并用于3步方法,用于海洋颜色数据的区域处理。 L1P步骤由辐射射线和几何系统校正组成,以及包括云筛选,太阳闪烁风险屏蔽或浮动植被检测的大气映射分类。第二步骤包括大气校正,并提供L2R产品,其包括具有误差表征和归一化的海洋反射。第三步是水处理,产生IOPS,衰减系数和水成分浓度。这些步骤中的每一个都将受益于OLCI上的附加频段。 5分量生物光学模型将用于OLCI的标准ESA处理,也是像素分类方法的一部分将是标准产品的一部分。其他算法适配正在准备。 CoastColour方法的另一个重要优点是高度可配置的处理链,其允许适应感兴趣区域,时间窗口,算法参数和处理链配置的各个特征。这种灵活性通过CoastColour按需处理服务提供给数据用户。完整的全局MeriS完整和降低的分辨率数据存档是可访问的,涵盖从2002年5月17日到08年5月17日的时间范围。2012年4月,这几乎是200TB的内置数据在线提供。 CoastColour按需处理服务可以作为托管处理的模型,其中软件被移动到数据,而不是将数据移动到用户,这将是来自来自Sentinel 3的大量数据的挑战。

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